Mutational heterogeneity in human cancers origin and consequences pdf

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mutational heterogeneity in human cancers origin and consequences pdf

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The incidence and mortality of lung cancer have increased steadily worldwide in the past several decades 1. In the previously published literature, we confirmed a number of factors associated with LUAD 3.

Clinical relevance of mutant-allele tumor heterogeneity and lung adenocarcinoma

The incidence and mortality of lung cancer have increased steadily worldwide in the past several decades 1. In the previously published literature, we confirmed a number of factors associated with LUAD 3. However, for LUAD, we still have a lot of unknown. For this reason, we need better tools to describe the characteristics of LUAD and predict the prognosis.

Several studies have shown that tumors are considered to be derived from the conversion of multiple genes in normal cells 4. This mutation exists in the entire process of tumor formation while these cells will continue to mutate in the tumor 4. ITH denotes the coexistence of subpopulations of cancer cells that differ in their genetic, phenotypic or behavioral characteristics within a given primary tumor, and between a given primary tumor and its metastasis 5.

There are many theories to explain the formation and function of ITH. A reasonable explanation is that tumor development is a Darwinian evolutionary process 6 , involving the interplay between cancer sub-clones and the local immune microenvironment. Mutual mutations and evolution between tumor cells cause changes in ITH. Thereby, the tumor develops in a direction favorable to its survival and enhances its drug resistance.

The more heterogeneous a tumor has the greater potential for its evolution, the stronger its ability to survive. The category of ITH includes linear, branching, neutral, punctuated and mixed 7. Mutated cells produce clones inside the tumor and counting these clones can detect heterogeneity. In general, greater genetic heterogeneity may cause worse prognosis.

This diversity can be attributed to genetic and epigenetic factors and non-hereditary mechanisms such as adaptive responses or fluctuation in signaling pathways.

Larger genetic heterogeneity can contain many subtypes. These are more likely to include some genotypes that are more capable of transferring more resistant and more. This means that highly heterogeneous tumors may be detrimental to drug resistance and easier to metastasize 8 - In other words, it is easier to make the tumor to develop a worse direction. Making tumors more prone to adverse mutations. Unfortunately, there is currently not a particularly good standard for assessing heterogeneity, so new approaches to assessing heterogeneity are imminent.

Unlike other single-cell heterogeneity evaluations, which are directed at the detection of the overall heterogeneity of a tumor At the same time, its requirements for the organization are simple. The distribution of mutant-allele fractions among loci thus provides a straightforward measure of one type of ITH, called mutant-allele tumor heterogeneity MATH We noticed that intra-tumor heterogeneity ITH noted in a range of tumor types. A measure of this ITH might provide clinically significant information.

Genetically distinct subpopulations of cells in a tumor lead to differences among mutated loci in terms of the fraction of sequence reads that show a mutant allele and the role of MATH in many recent cancers has been revealed.

In head and neck squamous cell carcinoma, MATH is mainly associated with disruptive TP53 mutations, human papillomavirus HPV status and increasing exposure to cigarette smoke. All patients have complete clinical information and follow-up information. The median absolute deviation MAD is a robust measure of the sample bias for univariate numerical data. It is also a population parameter about the sample.

For the univariate datasets X1, X2, The calculation of MAD is followed the default in R, with values scaled by a constant factor 1. MATH primarily indicates the width of the center ratio of mutant allele fractions in the tumor-specific mutation loci.

Each patient used in this article has a clear relevant data and follow-up information. In order to exclude interference from non-tumor-related factors in the study, we excluded the follow-up data eight years after the operation. Figure 1 shows some MATH related information. The chart shows that the distribution of MATH generally tends to be a normal distribution.

At the same time, we intuitively demonstrated a relationship between MATH and age, gender, race and stage.

In the meantime, in order to clarify the clinical information related to MATH and better guide clinical application, we divided the study into two groups according to the median MATH value After comparison, we found some clinical information related to MATH. People with high MATH are more likely to be women and more likely to smoke. This is in line with our clinical expectations and has great guiding significance for the prognosis.

NGS is already a very mature technology, and it has also begun to be gradually applied clinically. Based on NGS, we also got a lot of information that we have not mentioned before Unlike other methods, MATH does not depend on a particular gene.

The relationship between MATH and the clinical features and prognosis of tumors has given MATH great potential as a clinical and scientific marker of tumors. The significance of MATH in head and neck cancer and breast cancer has been reported, and its use in lung cancer has great potential.

Therefore, we used the TCGA database to study its role in adenocarcinoma. At first, we study the distribution of MATH. It tends to be normally distributed. This visually shows its distribution in the crowd. In addition, we found that their MATH values were significantly higher than those of head and neck squamous cell carcinoma and breast cancer.

This indicates that lung cancer is more heterogeneous than head and neck squamous cell carcinoma and breast cancer, suggesting that lung cancer in the prognosis, metastasis, resistance and other aspects generally worse than the head and neck squamous cell carcinoma and breast cancer. This can still be mutually verified in our general conclusion. On the other hand, it explains the particularity of lung cancer. We also visually demonstrated a relationship between MATH and age, gender, race and staging.

Clinical features make sense for our clinical reference. Here, we found that people who smoked more MATH values, which may be interpreted as smoking as a recognized influencing factor, also had an impact on tumor internal heterogeneity. The existence of this effect in adenocarcinomas has important clinical implications. Especially for the application of TKI drugs can have some guidance. In addition, regarding the relationship between TKI resistance and MATH, we think it is necessary to conduct future clinical trials to conduct research.

One of the biggest purposes of clinical treatment is to improve the prognosis and to judge the prognosis of different patients especially in the increasingly popular NGS using today, the use of NGS to help clinically is a very meaningful medical behavior. In the current study, complete, long-term follow-up is relatively lacking.

However, the importance of follow-up is beyond doubt, so we chose the TCGA database for research. At the same time, for different MATH worthy of patients we should also be flexible use of surgical radiotherapy and chemotherapy for treatment.

In chemotherapy, the tumor can also be based on the level of heterogeneity to the most appropriate selection of the most appropriate drug combination in order to achieve the purpose of personalizing precision medical treatment, improve efficacy and reduce adverse reactions. The shortcoming of this method lies in its complete dependence on NGS.

Meanwhile, the relationship between specific MATH and medication also needs further clinical trials. At the same time, we can retrospectively conduct NGS based on the results of existing clinical trials to study the specific effects of various methods such as drugs, surgery and radiotherapy under various MATH values.

This deserves our further consideration. This study does not involve any non-public patient data. The author is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Figure 1 Distribution of the mutant-allele tumor heterogeneity MATH value and its relationship with clinical factors. C,D,E Relationship between gender, race, and T stage.

Cite this article as: Mao H. Clinical relevance of mutant-allele tumor heterogeneity and lung adenocarcinoma. Ann Transl Med ;7 18

Epigenetic heterogeneity in cancer

Although not all somatic mutations are cancer drivers, their mutational signatures, i. However, the mechanisms underlying nearly one-third of all mutational signatures are not yet understood. The signatures with established etiology and those with hitherto unknown origin appear to have some differences in strand bias, GC content and nucleotide context diversity. While nucleotide contexts might be adequate to establish etiologies of some mutational signatures, in other cases additional features, such as broader epi genomic contexts, including chromatin, replication timing, processivity and local mutational patterns, may help fully understand the underlying DNA damage and repair processes. Nonetheless, remarkable progress in characterization of mutational signatures has provided fundamental insights into the biology of cancer, informed disease etiology and opened up new opportunities for cancer prevention, risk management, and therapeutic decision making. Genomic instability is a hallmark of all cancers. Cancer genomes typically harbor 10 3 —10 5 somatic point mutations, along with other classes of genomic alterations, including insertions and deletions InDels , copy number variations, rearrangements and ploidy changes 1 , 2.

International Journal of Biological Sciences. Journal of Cancer. Journal of Genomics. Global reach, higher impact. Journal of Genomics - Submit manuscript now

Metrics details. Phenotypic and functional heterogeneity is one of the hallmarks of human cancers. Tumor genotype variations among tumors within different patients are known as interpatient heterogeneity, and variability among multiple tumors of the same type arising in the same patient is referred to as intra-patient heterogeneity. Subpopulations of cancer cells with distinct phenotypic and molecular features within a tumor are called intratumor heterogeneity ITH. Since Nowell proposed the clonal evolution of tumor cell populations in , tumor heterogeneity, especially ITH, was actively studied. Research has focused on the genetic basis of cancer, particularly mutational activation of oncogenes or inactivation of tumor-suppressor genes TSGs.

Mutational Heterogeneity in Human Cancers : Origin and Consequences

The system can't perform the operation now. Try again later. Citations per year. Duplicate citations.

Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. The risk of developing certain cancers can be reduced by not smoking, maintaining a healthy weight, limiting alcohol intake, eating plenty of vegetables , fruits , and whole grains , vaccination against certain infectious diseases, limiting consumption of processed meat and red meat , and limiting exposure to direct sunlight. In , about Greek physicians Hippocrates and Galen, among others, noted similarity of crabs to some tumors with swollen veins.

The sheer size of the human genome makes it improbable that identical somatic mutations at the exact same position are observed in multiple tumours solely by chance. The scarcity of cancer driver mutations also precludes positive selection as the sole explanation. Therefore, recurrent mutations may be highly informative of characteristics of mutational processes. We describe each genome with 13 recurrence-based and 29 general mutational features.

Molecular heterogeneity in lung cancer: from mechanisms of origin to clinical implications

Despite numerous advances in cell biology, genetics, and developmental biology, cancer origin has been attributed to genetic mechanisms primarily involving mutations. Embryologists have expressed timidly cancer embryological origin with little success in leveraging the discussion that cancer could involve a set of conventional cellular processes used to build the embryo during morphogenesis. The concept of environment is often used with a broad scope and includes all nongenetic factors such as diet, lifestyle, and infectious agents.

Introduction

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